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bayesPop: Probabilistic Population Projections

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  • Ševčíková, Hana
  • Raftery, Adrian E.

Abstract

We describe bayesPop, an R package for producing probabilistic population projections for all countries. This uses probabilistic projections of total fertility and life expectancy generated by Bayesian hierarchical models. It produces a sample from the joint posterior predictive distribution of future age- and sex-specific population counts, fertility rates and mortality rates, as well as future numbers of births and deaths. It provides graphical ways of summarizing this information, including trajectory plots and various kinds of probabilistic population pyramids. An expression language is introduced which allows the user to produce the predictive distribution of a wide variety of derived population quantities, such as the median age or the old age dependency ratio. The package produces aggregated projections for sets of countries, such as UN regions or trading blocs. The methodology has been used by the United Nations to produce their most recent official population projections for all countries, published in the World Population Prospects.

Suggested Citation

  • Ševčíková, Hana & Raftery, Adrian E., 2016. "bayesPop: Probabilistic Population Projections," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 75(i05).
  • Handle: RePEc:jss:jstsof:v:075:i05
    DOI: http://hdl.handle.net/10.18637/jss.v075.i05
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    References listed on IDEAS

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    1. Adrian E. Raftery & Le Bao, 2010. "Estimating and Projecting Trends in HIV/AIDS Generalized Epidemics Using Incremental Mixture Importance Sampling," Biometrics, The International Biometric Society, vol. 66(4), pages 1162-1173, December.
    2. Adrian E. Raftery & Nevena Lalic & Patrick Gerland, 2014. "Joint probabilistic projection of female and male life expectancy," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(27), pages 795-822.
    3. Ševčíková, Hana & Alkema, Leontine & Raftery, Adrian, 2011. "bayesTFR: An R package for Probabilistic Projections of the Total Fertility Rate," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i01).
    4. Hyndman, Rob J. & Shahid Ullah, Md., 2007. "Robust forecasting of mortality and fertility rates: A functional data approach," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4942-4956, June.
    5. Leontine Alkema & Adrian Raftery & Patrick Gerland & Samuel Clark & François Pelletier & Thomas Buettner & Gerhard Heilig, 2011. "Probabilistic Projections of the Total Fertility Rate for All Countries," Demography, Springer;Population Association of America (PAA), vol. 48(3), pages 815-839, August.
    6. Camarda, Carlo G., 2012. "MortalitySmooth: An R Package for Smoothing Poisson Counts with P-Splines," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 50(i01).
    7. David Sharrow & Samuel J. Clark & Mark Collinson & Kathleen Kahn & Stephen Tollman, 2013. "The age pattern of increases in mortality affected by HIV," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(39), pages 1039-1096.
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    1. Raftery, Adrian E. & Ševčíková, Hana, 2023. "Probabilistic population forecasting: Short to very long-term," International Journal of Forecasting, Elsevier, vol. 39(1), pages 73-97.
    2. Guy Abel, 2018. "Non-zero trajectories for long-run net migration assumptions in global population projection models," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 38(54), pages 1635-1662.
    3. Phoebe Koundouri & Georgios I. Papayiannis & Achilleas Vassilopoulos & Athanasios Yannacopoulos, 2022. "A general framework for the generation of probabilistic socioeconomic scenarios and risk quantification concerning food security with application in the Upper Nile river basin," DEOS Working Papers 2203, Athens University of Economics and Business.
    4. Phoebe Koundouri & Georgios I. Papayiannis & Achilleas Vassilopoulos & Athanasios N. Yannacopoulos, 2023. "Probabilistic Scenario-Based Assessment of National Food Security Risks with Application to Egypt and Ethiopia," Papers 2312.04428, arXiv.org, revised Dec 2023.
    5. Jessica Godwin & Adrian E. Raftery, 2017. "Bayesian projection of life expectancy accounting for the HIV/AIDS epidemic," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 37(48), pages 1549-1610.
    6. Aral, Mustafa M., 2020. "Knowledge based analysis of continental population and migration dynamics," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    7. Michael Pearce & Adrian E. Raftery, 2021. "Probabilistic forecasting of maximum human lifespan by 2100 using Bayesian population projections," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(52), pages 1271-1294.

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